From designing production-grade RAG pipelines to evaluating frontier models for enterprise use cases, my work is grounded in real engineering and practical outcomes, not hype.
Retrieval-Augmented Generation — RAG pipelines, chunking strategies, embedding selection, reranking, and evaluation frameworks.
Agentic Systems — Multi-step agents with tool use, state management, memory, and orchestration.
Model Evaluation — Rigorous eval frameworks for benchmarking LLMs against specific use cases and detecting regressions.
Enterprise AI Adoption — Governance, change management, and building internal AI capability from scratch.
Fine-tuning & Alignment — Instruction tuning and RLHF-style techniques; knowing when fine-tuning beats prompting.
Responsible AI — Hallucination mitigation, bias detection, prompt injection guardrails, and production monitoring.
| Category | Tools |
|---|---|
| Models | Claude, GPT-4 / o-series, Gemini, Llama, Mistral |
| Frameworks | LangChain, LangGraph, LlamaIndex, Hugging Face |
| Infrastructure | Pinecone, Qdrant, pgvector, AWS Bedrock, Azure OpenAI |
| Evals & Ops | Braintrust, Langsmith, PromptLayer |